Physical sensors are used in many modern machines to measure and monitor physical phenomena, such as temperature, speed, and fluid flow constituents. Physical sensors often take direct measurements of the physical phenomena and convert these measurements into measurement data to be further processed by control systems. Although physical sensors take direct measurements of the physical phenomena, physical sensors and associated hardware are often costly and, sometimes, unreliable. Further, when control systems rely on physical sensors to operate properly, a failure of a physical sensor may render such control systems inoperable. For example, the failure of an intake manifold pressure sensor in an engine may result in shutdown of the engine entirely, even if the engine itself is still operable.
Instead of direct measurements, virtual sensors are developed to process other physically measured values and to produce values that were previously measured directly by physical sensors. For example, U.S. Pat. No. 5,386,373 (the '373 patent) issued to Keeler et al. on Jan. 31, 1995, discloses a virtual continuous emission monitoring system with sensor validation. The '373 patent uses a back propagation-to-activation model and a monte-carlo search technique to establish and optimize a computational model used for the virtual sensing system to derive sensing parameters from other measured parameters.
The techniques disclosed in the '373 patent may not account for certain physical limitations of the sensor environment and/or the physical sensor it is replacing, and thus may provide inaccurate values. For example, the rate of change of a machine's parameter values may be limited by the machine's physical characteristics, e.g., the rate of change in the speed of a motor may be limited by physical constraints such as weight, inertia, friction, etc. Thus, the speed of the motor is unlikely to be able to change from 0 revolutions per minute (rpm) to 3000 rpm in 0.1 seconds. However, a virtual sensor that is unconstrained and bases its output parameter values on other input values may generate output parameter values that indicate the occurrence of such an implausible scenario. Thus, it may be desirable to control the output parameter values of the virtual sensors in such a way as to ensure that a rate of change of the output parameter values is feasible based on the physical characteristics of the machine and/or the physical sensor that is being modeled by the virtual sensor.
The disclosed methods and systems are directed to solving one or more of the problems set forth above and/or other problems of the prior art.